The invention relates to apparatus and methods for efficiently maintaining, evaluating and managing the physical state or condition of assets and, more particularly, apparatus and methods for xe2x80x9cratingxe2x80x9d asset conditions, estimating asset service life and providing data for facilitating alternative repair/replacement decisions.
Commercial, industrial and other types of organizations must continuously be concerned about the business xe2x80x9cconditionxe2x80x9d of their organizations. Such concerns typically involve business decisions regarding sales, marketing, advertising and numerous other issues. Also, these concerns may involve relatively xe2x80x9ctangiblexe2x80x9d issues such as existing and future space requirements, future employee growth (or reduction), necessary equipment purchases and similar concerns. For purposes of forecasting space requirements, requisite employee hiring requirements and new equipment purchases, along with similar issues involving current and future growth and expenditures, various activities of differing xe2x80x9csophisticationxe2x80x9d can be undertaken.
For example, it is common for industrial and commercial establishments to undertake xe2x80x9cforecastingxe2x80x9d activities directed to prediction of future expectations as to the general economy and the economic expectations of the specific business in-which the individual organization is involved. In fact, a number of management consultant firms specialize in such undertakings. Also, various types of business forecasting xe2x80x9cmodelsxe2x80x9d have been developed in an attempt to more accurately predict the future state of the general economy and the future state of specific types of businesses. These forecasting models are often in the form of computer software packages and the like, whereby various types of algorithms are utilized to predict future economic status, based on input data comprising various financial and demographic variables. The software packages can be in the form of computer programs licensed or sold directly to business organizations or alternatively, may comprise software packages maintained proprietary and internally by financial and other business management consultants.
Such forecasting models typically utilize a number of variables in attempting to more accurately predict future business conditions. For example, a business forecasting model for a specific organization may take into account the geographic location of the business, expected population growth around the location, xe2x80x9cagexe2x80x9d of the specific business or technology in which the organization is involved, parameters indicative of future product or service demands, and many other variables. Through the use of these models, it is possible for a commercial or industrial organization to predict, within finite confidence limits, the expected growth of the demand for the organization""s products or services and, therefore, the expected potential growth (or reduction) of the organization""s business.
More specifically, financial and other business management consultants can use the business forecast to estimate future sales of the organization""s products or services, given that certain purchases of physical plant, other equipment and similar assets required for such sales are undertaken. Correspondingly, assuming certain levels of product sales or services are attained, an organization can estimate its expected revenues. Similarly, assuming certain employee growth and equipment and plant purchases, an organization can estimate future expenses relating to such items. With all this information, income, cash flow and other financial matters can be reviewed and analyzed to determine suitable activities to be undertaken by a business organization with respect to its growth.
The foregoing description of an organization""s future business concerns, and the proceedings undertaken to predict the economic future and potential business growth, are relatively well known. However, in addition to concerns about space requirements, equipment purchases, employee hiring and the like commercial and industrial organizations have other xe2x80x9cinherentxe2x80x9d items which may have a significant impact on future expenses. Among these items is the actual physical condition of existing physical plant components.
That is, the expenses associated with repair and/or replacement of currently existing physical plant components can have a significant impact on the financial status of an organization. For example, it can be assumed that a small or medium sized business organization is involved in the assembly and manufacture of a product requiring a relatively large number of machined parts which are produced at the organization""s own facilities. The facilities may thus comprise a factory or a single building of relatively large floor space. If such facilities are relatively old, significant repairs or replacement may be required of plant items such as a main heating, ventilation and air conditioning (HVAC) system. Correspondingly, the costs associated with such repairs or replacement may significantly affect the organization""s financial status, notwith-standing that repair or replacement expenses may be amortized over the remaining useful life of the repaired or new system. That is, notwithstanding amortization, a business organization may be required to have a relatively large amount of cash available immediately for such repairs or replacement. It is not uncommon for typical business forecasting models to substantially xe2x80x9cignorexe2x80x9d required expenditures for repair or replacement of existing plant structures.
Furthermore, with respect to repairs or replacement of plant facility components, it is not uncommon for a business organization to have a number of alternative activities available which may be undertaken. Returning to the example of the HVAC system described above, an alternative to replacement of the entirety of the system may be replacement of only a selected number of individual components of the system, with less expenditures associated with such selective replacement. Still further, the entirety of the system may be repaired, as a substitute for replacement of any substantive components. Adding another layer of complexity to the repair or replacement decision process is the further alternative of selective repair of components, with deferral of other repair options. As an example, a business organization may choose only to effect xe2x80x9cemergencyxe2x80x9d repairs of system defects, i.e., repairs of defects which must be made immediately to avoid potential production downtime, or a similar deleterious events.
Each of the foregoing decisions may have significantly different impacts on the financial status of the business organization, relative to other potential decisions. In addition, some of the repair or replacement decisions may be financially unfeasible, given current budget restraints or lack of expected cash flow. Further, it is relatively easy for a financial planner to make a decision for repair of plant facility components, rather than replacement, in view of the fact that such repairs may xe2x80x9cappearxe2x80x9d to be significantly less expensive in the near future. However, if such repairs do not sufficiently increase the xe2x80x9cuseful lifexe2x80x9d of the system components, or the entirety of the plant system, the actual cost to the business organization in the long term may be substantially greater than the long-term cost of a replacement option.
A further problem exists with respect to the impact of repair or replacement decisions on the xe2x80x9capparentxe2x80x9d financial status of a business organization. For example, a business-organization may have a plant facility system, such as the aforedescribed HVAC system, currently being amortized over its useful life. Immediately following the end of its useful life, and depletion of the system as an asset on the financial records of the business organization, significant repairs or replacement may be required. However, by deferring repairs or other maintenance, the business organization may be able to show an apparent xe2x80x9cpositivexe2x80x9d effect on its financial records. That is, the xe2x80x9cexpensesxe2x80x9d represented by asset depreciation in prior fiscal years will no longer be present after asset depletion. The effect of the deferred maintenance can thus result in an apparent (and actually erroneous) reduction of organization expenses for the current fiscal year.
It should be noted that tax and other accounting governing organizations have recognized the foregoing problems, and efforts are currently being made to develop new and more realistic procedures for evaluation and depletion of capital assets. For example, accounting procedures are being considered which would require business organizations to report xe2x80x9ccostsxe2x80x9d of deferred maintenance. With the current accounting procedures, and with deferred maintenance following asset depletion, the xe2x80x9cvaluexe2x80x9d of a business organization can be potentially xe2x80x9coverstated.xe2x80x9d That is, a xe2x80x9cquick profitxe2x80x9d can be shown by a business organization merely by deferring maintenance of significant depleted capital assets.
Keeping the foregoing in mind, it is apparent that a xe2x80x9cmodelxe2x80x9d of the current xe2x80x9cstatusxe2x80x9d or xe2x80x9cconditionxe2x80x9d of physical plant assets would be useful in selecting among various repair or replacement options which may be undertaken. However, a first requirement for, in some manner, quantifying the xe2x80x9cconditionxe2x80x9d of a plant facility component is to develop a procedure for xe2x80x9cratingxe2x80x9d the component condition. That is, it is first necessary to determine parameters representative of the physical condition of the component. Further, such parameters must be capable of, or be based upon, physically realizable measurements.
These parameters could potentially take the form of parameters representative of specific xe2x80x9cdefectsxe2x80x9d apparent from the physical appearance of the component, or the mechanical (or, even possibly, electrical) operation of a component, if the component is a machine or like device. In any event, parameters representative of component xe2x80x9cproblemsxe2x80x9d would necessarily be required to be representative of the overall component condition.
Secondly, such xe2x80x9cproblem-representativexe2x80x9d parameters could potentially be of varying degrees. That is, assuming that a parameter relevant to and representative of the condition of a component is determined, the degree of severity of the problem parameter may have an impact on the component condition.
In addition to the requirement of quantifying the xe2x80x9cratingxe2x80x9d of the component condition, it would be necessary to further quantify the impact of the rating parameters on the future useful life of the component. That is, the effect of the rating parameters on future xe2x80x9cintegrityxe2x80x9d of the component would be of necessity. Clearly, for a model to provide a basis for decision making related to alternative repair or replacement options, the effect of the parameters on xe2x80x9cservice lifexe2x80x9d must be determined.
However, one problem associated with rating the condition of a component and estimating service life based on parameter measurements is that each parameter measurement will likely affect the impact of another parameter measurement. That is, parameters or variables representative of asset condition are typically not xe2x80x9cindependent.xe2x80x9d For example, if two different types of severe defects were discovered during the measurement process, the impact on service life may have a synergistic effect, relative to the service life impact of solely one or the other defects. More specifically, impact on service life of two different types of defects could not likely be quantified merely as an additive process. Accordingly, a significant level of complexity may exist in the condition rating process with respect to multiple parameters.
Further, the impact of a xe2x80x9ccondition-indicatingxe2x80x9d parameter may be somewhat dependent on differences of xe2x80x9csub-elementsxe2x80x9d of similar assets. For example, when attempting to rate the condition of an HVAC system, the severity of impact on the service life of the system as indicated by the condition of electrical wiring in the system may be dependent on the operating voltage of system motors. Again, this dependency among condition-indicating parameters and the specific types of components comprising the asset adds still further complexity to the condition rating process.
To ideally rate the condition of a component, estimate service life and provide a basis to select repair or replacement options would be a relatively enormous undertaking. Such a procedure would require the capability of determining the specific and exact impact of parameters measured by ideal instrumentation on the condition and service life estimation of the component. Such measurements would necessarily include combinations of problem defects and severity levels. It is apparent that such an approach, even if feasible and physically realizable, would require very extensive and expensive research and field testing.
In accordance with the invention, an asset management system is adapted to provide an empirical quantitative analysis of the condition of a physical and structural asset, and allow a user to evaluate the effect of potential repair/replacement activities on the condition of the asset. The system includes data entry means responsive to manual or automated entry of data representative of problems or defects associated with the asset. First storage means are adapted to receive and store the data representative of the problems or defects, and also to store data representative of generic information associated with the asset.
First processing means are utilized to process the data representative of the problems or defects, and generate condition factor signals representative of a figure of merit of the condition of the asset. Second processing means are utilized to process data representative of the generic information, and generate serviceability estimate signals representative of the anticipated useful life of the asset, based upon the condition factor signals and the generic information.
Second storage means comprise financial data representative of the costs of repairs of defects of the asset, and the costs of replacements of the asset. Third processing means are responsive to input data from the user, and data stored in the first and second storage means, to generate modified condition factor and serviceability estimate signals representative of a modified figure of merit of the condition of the asset, and a modified anticipated useful life of the asset, based upon user input data representing an assumption of repairs of one or more defects, or replacement of the asset or individual components thereof. Further, the third processing means is also adapted to generate financial data representative of the financial impact of assumed repairs or replacements on the value of the asset, so as to allow the user to compare repair and replacement alternatives with respect to financial impact.